Encoder-side synonym fuzzing and decoder-side log-likelihood probes lose discriminative power on large dense code LLMs, while reversible I/O transforms show scaled models preserve algorithmic structure and fail mainly on output serialization.
In: Proceedings of the 61st Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers), pp
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Memorization Diagnostics for Code LLMs Should be Scale-Aware
Encoder-side synonym fuzzing and decoder-side log-likelihood probes lose discriminative power on large dense code LLMs, while reversible I/O transforms show scaled models preserve algorithmic structure and fail mainly on output serialization.